Ontology-based Context-sensitive Computing for FMS Optimization

Date: March, 2012

Linked to: RTD research and

Self-learning project at FAST

Contact Information

Tampere University of Technology,

FAST Laboratory,

P.O Box 600,

FIN 33101, Tampere,

Finlnad

Email: fast@tut.fi

Web: www.tut.fi/fast

 

Journal: Assembly Automation, Vol. 32, Issue 2,

pp.163-174, ISSN: 0144-5154

Title of the Paper: Ontology-based Context

-sensitive Computing for FMS Optimization

Authors: M. Kamal Uddin, J. Puttonen, S.Scholze,

A. Dvoryanchikova, J.L. Martinez Lastra

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original paper, please contact us

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Outline

Introduction and Background: Context-Sensitive Computing and Ontologies in Manufacturing

Methodology: Context-Sensitive Computing for FMS Optimization• Context model Development• Context management• A Framework: Context-Sensitive computing for FMS optimization

FMS Use case implementation

Conclusions and Future work

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Introduction

FMS Plants are associated with • Chaotic job processing orders• Unscheduled events at run time• Lack of transperency of complex machines/processes

Plants states are isolated and cannot be fully understood since there is a lack of infrastructure providing explicit manufacturing knowledge

Modern FMS plant utilizes complex control architectures, promoting integration of various decision support applications

Context-sensitive support applications are emerging in different areas of manufacturing for providing runtime decision support and,

Ontology-based context-sensitive computing is the top candidate paradigm to provide optimization support for modern FMS plants

4Background: Ontology-based Context Modeling and Applications in Manufacturing

Ontologies allow context modeling at a semantic level, establishing a common understanding of terms and enabling context sharing, logic inference, reasoning and reuse in a distributed environment

Recent advancement of context-aware computing and Ontologies in manufacturing enables a common language for sharing manufacturing product, process and system knowledge among designers and software applications

Domain ontologies to capture the manufacturing knowledge to define their structure and relations in a hierarchical manner

Formally represented domain knowledge facilitate knowledge sharing/ reuse and infer new knowledge utilizing relations and axioms built in ontologies

With the advent of Web-based software applications in manufacturing and especially SWSs, research on context-awareness and ontologies are emerging

5Methodology: Ontology-based Context Model Development (1/3)

Process Domain

Product Domain

Resource Domain

Device Domain

6Methodology: Context Management Process (2/3)

Conceptual context management process

Context identification Process

Ontological reasoning

Identified Context Domain

Specific Rule-Based Reasoning

Statistical Reasoning

Refined Context

Context Reasoning

7Methodology: A Famework, Context-Sensitive Optimization for FMS (3/3)

8FMS Use Case Implementation: Overview (1/4)

•A FMS use case, producing assembly parts (e.g. industrial robots, hydraulic components, aircraft parts) for automotive industries

•Control system architecture is based on SOA principles, where all the production relevant entities offer web services (WS) to a Microsoft.Net-based control platform

•A control application software runs the FMS in real time invoking data from available services (WSDL files)

•The application contains a set of master data for product manufacturing and simulated process devices to run the operations in a simulated environment

•Pallets are utilized as the job carrying entity to the loading stations and machining cells

FMS Use Case Implementation: Approach (2/4)

• Context-sensitive information model: An Ontology-based context model is developed for context extraction from SOA platform

• The interfacing to the SOA control platform is done by creating Java applications that invoke the web services of the control application to monitor the status of the production system

• WSs invocation is implemented through dedicated client applications applying client stub code from the WSDL description

• Invoked services are: manufacturing cell service, loading station service, machine pallet service, manufacturing process service, manufacturing template repository service and NC program library service to extract contextual entities

• To extract the contextual entities from the running services in SOA platform, different Java classes are implemented to invoke services and create object model for storing the monitoring data, to analyse obtained monitoring data and create corresponding OWL individuals to populate the context model

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FMS Use Case Implementation: Context-sensitive information model (3/4)

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FMS Use Case Implementation: Context Extraction and Populating the Context Model (4/4)

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Conclusions and Future Work

• The paper presents a modular approach of context-sensitive computing to achieve optimization to the dynamic operating environment of FMS. The context model development and the context management approach provides a common interface for context acquisition, reuse and updates, which are utilized by desperate client applications for runtime optimal decision making

• The core functional requirements of context-sensitive computing as the context modelling using OWL ontologies, WS-based interfacing for SOA control platform, runtime extraction of contextual entities, populating and updating of the dynamic entities to the context model are implemented within a practical FMS use case

• The next steps of this work will address higher level implementation of the presented framework for ontology-based context-sensitive computing for FMS optimization. High level context processing through context management will be implemented. An optimization algorithm will be developed, which will utilize the runtime KPI relevant contexts to provide proactive optimal suggestions to a separate UI

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